Rapid evolutionary change in trait correlations of single proteins

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability – the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein’s ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

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Field-specific reporting To study how trait correlation evolves through mutation and selection, we subjected populations of yellow fluorescent protein (YFP) and VIM2 metallo-beta-lactamase to directed evolution under different selection strengths.We then quantify how mutations and selection shape the correlations between two traits in the fluorescent protein populations (the ability to emit yellow and green light) and between three traits in our enzyme populations (the resistance against ampicillin, cefotaxime, and meropenem).Through engineering mutants and biochemical assays, we revealed that mutation and selection can drive the evolution of trait correlation by shaping protein foldability (a protein's ability to fold).
We did not perform a statistical test to pre-determine the sample size.However, we ensured an appropriate number of biological replicates based on the magnitude and consistency of measurable differences between groups.The sample sizes for all measurements are described in the figure legends.
We performed data collection using computer softwares.We used excel sheets to record fluorescent data.We used .fcsfiles to record the output of FACS library sorting.We used pen and paper to write down the number of counted colonies.
Data collection for AMP, CTX and MEM MICs happened intermittently between 06'2018-08'2021, with a frequency of once every 1-2 months based on when the mutant libraries were generated.We kept the number of colonies on the plate used for selection to 20,000, and sampled between 24-96 variants from every 5-10 libraries.No samples were excluded from the analysis.
All measurements were performed at least in three biological replicates.
We did not perform randomization as this procedure is not relevant for our study.We selected all surviving colonies for our VIM2 experiments and hence did not require a randomized selection.Also, the FACS experiments generate cells that are all sorted into different bins.We selected all the bins in these experiments without the need to randomization.This procedure is not relevant for our study.As the surviving colonies carrying different enzyme variants after ampicillin selection had similar colony sizes, we had no way of pre-assessing the resistance strength of colonies picked for AMP/CTX/MEM MIC characterization, thus the process of picking colonies from the plate was randomized and did not need blinding to the conditions.
The quantification of soluble fluorescent proteins in evolving populations was performed using a GFP ELISA Kit (AKR-121, Cell Biolabs Inc.).
For the GFP ELISA Kit, please refer to https://www.cellbiolabs.com/sites/default/files/AKR-121-gfp-elisa-kit.pdfNA NA NA We used the 3D structure of VIM2 with the pdb id=4BZ3 (https://www.rcsb.org/structure/4BZ3)for structure visualization.We used previously published deep mutational scanning data of VIM2 for trait correlation analyses performed on mutational data (raw data available at: BioProject ID PRJNA606894, processed data available at: https://cdn.elifesciences.org/articles/56707/elife-56707-supp2-v2.xlsx) Please select the one below that is the best fit for your research.If you are not sure, read the appropriate sections before making your selection.For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdfEcological,evolutionary& environmental sciences study designAll studies must disclose on these points even when the disclosure is negative.
There was a pause in data collected between 01'-05'2019 and 09'2019-08'2020 for attending courses.Data collection for YFP was conducted from 2016 to 2021 and from 2018 to 2023 respectively.Jia Zheng and Pouria Dasmeh recorded the data for YFP experiments.Ayse Erdogan recorded the data from VIM2We require information from authors about some types of materials, experimental systems and methods used in many studies.Here, indicate whether each material, system or method listed is relevant to your study.If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.